Socioeconomic and recharge effect on spatial changes in the groundwater chemistry of Punjab, Pakistan: a multivariate statistical approach

Khan, Mumtaz; Khan, Wajid

doi:10.1007/s42452-020-03255-3

Cited by 7 publications

(1 citation statement)

References 64 publications

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“…The irrigated area of Multan is very highand salinity is also highest in the province (Figure 2). The Central Punjab is highly polluted followed by Southeast Punjab as reported by Khan and Khan, 2020. The results indicated that salinity and area under wheat has inverse relationship.…”

Section: Resultsmentioning

confidence: 79%

Dynamics of Salinity and Land Use in Punjab Province of Pakistan

Malik¹,

Tayyab²,

Ullah³

et al. 2021

PJAR

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T he agricultural sector support Pakistan's economy in provision of food for the 211.17 million people (GOP, 2020) and increasing with the pace of 2.10 percent per annum (World Bank, 2015). Over 800 m.ha. of land around the globe is salt-affected either saline or sodic soils or both), associating to over six percent of the land area of the globe (FAO, 2010). Furthermore, around 15 m. ha. of land faces yield reduction due to soil affected in less develop countries (Tilman et al., 2002). High salinity of soil is major environmental issue limiting thedevelopment of agriculture in coastal areas (Hillel, 2000;Yadav et al., 2011). Pakistan has atotal area of 79.6 millionhectare (mha), with 22.05 mha. cultivated land (GOP, 2020) and 6.28 mha affected by salt (GOP, 2012). Salinity has serious socioeconomic repercussions on agricultural communities of the country, which leads to affect living standard, rural urban migration, serious health issues, the collapsing of houses, and disturbing communications and transportation (Hollington, 2001). Selection and breeding for improved tolerance against salinity in different cropsis considered as high priority due to its economic benefits and best alternative. The other strategies to mitigate salinity are costly and unaffordable for the farming community (Ashraf, 2009).

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Section: Resultsmentioning

confidence: 79%

Dynamics of Salinity and Land Use in Punjab Province of Pakistan

Malik¹,

Tayyab²,

Ullah³

et al. 2021

PJAR

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Groundwater delineation for sustainable improvement and development aided by GIS, AHP, and MIF techniques

Ehsan,

Shabbir,

Al-Quraishi

et al. 2024

Appl Water Sci

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Exploration of groundwater is an integral part of viable resource growth for society, economy, and irrigation. However, uncontrolled utilization is mainly reported in urban and industries due to the increasing demand for water in semi-arid and arid regions of the world. In the background, groundwater demarcation for potential areas is vital in meeting necessary demand. The current study applied an integrated method comprising the analytical hierarchy process (AHP), multiple influence factors (MIF), combined with a linear regression curve and observatory well data for groundwater prospects mapping. Thematic maps such as flow direction, flow accumulation, elevation map, land use land cover, slope, soil texture, hill shade, geomorphology, normalized vegetation index, and groundwater depth map were generated utilizing remote sensing techniques. The relative weight of each parameter was estimated and then assigned to major and minor parameters. Potential zones for groundwater were classified into five classes, namely very good, good, moderate, poor, and very poor, based on AHP and MIF methods. A spatially explicit sensitivity and uncertainty analysis method to a GIS-based multi-criteria groundwater potential zone model is presented in this research. The study addressed a flaw in the way groundwater potential mapping results are typically presented in GIS-based multi-criteria decision analysis studies, where discrete class outputs are used without any assessment of their certainty with respect to variations in criteria weighting, which is one of the main contributors to output uncertainty. The study region is categorized based on inferred results as very poor, poor, marginal, and very good in potential ground quality 3.04 km2 is considered extremely poor, 3.33 km2 is considered poor, 64.42 km2 is considered very good, and 85.84 km2 is considered marginal zones, which shows reliable and potential implementation. The outcomes of AHP and MIF were validated by linear regression curve and actual water table in a study area. The study results help to formulate the potential demarcation of groundwater zones for future sustainable planning and development of groundwater sources. This study may be helpful to provide a cost-effective solution to water resources crises. The current study finding may be helpful for decision-makers and administrative professionals for sustainable management of groundwater resources for present and future demands.

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